README.md

metadata

license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
datasets:
  - xsum
metrics:
  - rouge
model-index:
  - name: theus_concepttagger
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xsum
          type: xsum
          config: default
          split: validation
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 34.8663

theus_concepttagger

This model is a fine-tuned version of facebook/bart-large-cnn on the xsum dataset. It achieves the following results on the evaluation set:

• Loss: 1.6249
• Rouge1: 34.8663
• Rouge2: 15.1526
• Rougel: 26.1224
• Rougelsum: 26.5164
• Gen Len: 62.4475

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.4096	1.0	12753	1.6249	34.8663	15.1526	26.1224	26.5164	62.4475

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3